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Zbl 1211.93108
Sakthivel, R.; Samidurai, R.; Anthoni, S.M.
Asymptotic stability of stochastic delayed recurrent neural networks with impulsive effects. (English)
[J] J. Optim. Theory Appl. 147, No. 3, 583-596 (2010). ISSN 0022-3239; ISSN 1573-2878/e

Summary: In this paper, the asymptotic stability for a class of stochastic neural networks with time-varying delays and impulsive effects is considered. By employing the Lyapunov functional method combined with the linear matrix inequality optimization approach, a new set of sufficient conditions is derived for the asymptotic stability of stochastic delayed recurrent neural networks with impulses. A numerical example is given to show that the presented result significantly improves the allowable upper bounds of delays over some existing results in the literature.

MSC 2000:: *93D20 Asymptotic stability of control systems
93B20 Minimal systems representations
93D30 Scalar and vector Lyapunov functions
60H10 Stochastic ordinary differential equations

Keywords: stochastic delayed recurrent neural networks; impulsive effects; linear matrix inequality optimization approach; global asymptotic stability; Lyapunov functional

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